Space instrumentation

Abstract:

This document is the EnVision Venus orbiter proposal, submitted in October 2016 in response to ESA's M5 call for Medium-size missions for its Science Programme, for launch in 2029. Why are the terrestrial planets so different? Venus should be the most Earth-like of all our planetary neighbours: its size, bulk composition and distance from the Sun are very similar to those of Earth. Its original atmosphere was probably similar to that of early Earth, with abundant water that would have been liquid under the young sun's fainter output. Even today, with its global cloud cover, the surface of Venus receives less solar energy than does Earth, so why did a moderate climate ensue here but a catastrophic runaway greenhouse on Venus? How and why did it all go wrong for Venus? What lessons can be learned about the life story of terrestrial planets in general, in this era of discovery of Earth-like exoplanets? Were the radically different evolutionary paths of Earth and Venus driven solely by distance from the Sun, or do internal dynamics, geological activity, volcanic outgassing and weathering also play an important part? Following the primarily atmospheric focus of Venus Express, we propose a new Venus orbiter named EnVision, to focus on Venus' geology and geochemical cycles, seeking evidence for present and past activity. The payload comprises a state-of-the-art S-band radar which will be able to return imagery at spatial resolutions of 1 - 30 m, and capable of measuring cm-scale deformation; this is complemented by subsurface radar, IR and UV spectrometers to map volcanic gases, and by geodetic investigations.

Abstract:

Ground test data in HDF5 and Matlab object formats from the ground testing of the Lunar Thermal Mapper instrument, 2023.

Abstract:

An accurate description of how visible light scatters from the lunar surface enables 1) constraints to be placed on the physical and compositional properties of the surface, using a photometric model such as the Hapke BRDF model, which has nine free parameters related to compositional and physical properties, and 2) more realistic scattering function inputs to be set within thermal models. Until a recent study by Foote et al. in 2010, lunar visible light scattering functions had been theoretically derived using limited laboratory measurements. Within thermal models, unrealistic scattering functions may be partly responsible for modelled temperature discrepancies of up to ~15-50 K (dependent on location)—when compared to remote sensing data from Diviner, onboard the Lunar Reconnaissance Orbiter—in regions such as polar craters, where light scattering due to surface topography dominates heat transfer. In this project, a laboratory goniometer setup was developed, which was used to measure a suite of visible light scattering functions for Apollo 11 (10084) and Apollo 16 (68810) lunar regolith samples across a wider range of viewing angles than has previously been measured. These samples were characterized in terms of their surface roughness and porosity profiles, and this enabled two of the free parameters within the Hapke BRDF model to be constrained. By fitting the model to the dataset, Hapke parameters could be deduced for the two representative (mare and highlands) regolith samples, and further constraints could be placed on the ‘practical’ size-scale of the model’s slope angle parameter. Thus, the dataset enabled Diviner’s visible-wavelength off-nadir data to be interpreted in a novel way, due to the reduction of free terms within the model. This led to surface roughness and compositional deductions (via the Hapke parameters h_s, b and θ ̅) for seven Diviner targets. Finally, the dataset was used to set more realistic scattering functions within the Oxford 3D Thermal Model, and it was demonstrated that this 1) could affect modelled high-latitude lunar surface temperature profiles by up to ~30 K—as compared to using previously assumed scattering functions—and 2) could increase the minimum depth at which water ice is predicted to be stable in the lunar subsurface by up to ~0.8 m. Hence, this dataset may help to constrain the possible distribution of water ice on the lunar surface, and this may be crucial for future lunar exploration missions such as Luna-27 and Artemis.